Data Science Experts in Stuttgart
matched in minutes from over 15,000 CVs with the power of AIHire experts who turn complex data into reliable forecasts, recommendation systems and decision tools using Python, SQL, machine learning and cloud platforms. FRATCH connects you quickly with vetted, available freelancers whose skills fit your project.
Meet FRATCH Experts in Stuttgart, who have recently used Data Science
Karin A.
Last position:
AI Benchmark Engineer | Native language specialist German at Lilt
- Task Engineering: Evaluating Coding Agents.
- Asset Creation: Building realistic task environments using datasets and files in German. Crucially, these assets must remain in the target language to genuinely measure multilingual handling.
- Prompting & Translation: finding failure points where AI does not work, in German.
- Implementation & Verification: Supporting the development of robust solutions (reference implementations) and write highly reliable, deterministic verifier scripts (using rubric-based judging only when strictly necessary).
- Calibration & Execution: Analyze execution logs and calibrate task difficulty (Easy to Very Hard) using standard Terminal-Bench run configurations against various model tiers (Haiku, Opus).
- Quality Assurance: Participation in a rigorous, 4-layer human quality control process (creation, human review, calibration review, and audit) alongside automated LLM-based checks to ensure fairness, grammatical accuracy, and benchmark integrity.
- Linguistic Review: Reviewing AI benchmark tasks across Hindi, Arabic, Japanese, Chinese, Czech and Turkish.
Mustafa Ö.
Last position:
Data & Business Analyst at Self-Employed / Freelancer
External consultant for various projects in the automotive industry.
Data-driven business and performance analysis
Analysis, interpretation and validation of complex business data
Identification of trends, risks and potential areas for improvement
Translation of analytical findings into actionable business recommendations
Preparation and presentation of results for business stakeholders
Chaima D.
Last position:
Data Scientist Intern at Marelli Automotive Lighting
- Developed and deployed a deep learning model for automated keypoint detection in headlamp light distributions.
- Prepared and processed datasets, and selected VGG16 after benchmarking CNN architectures for the best accuracy efficiency trade-off.
- Delivered a Flask REST API, containerized with Docker, and integrated the solution into an existing internal system, enabling automated and efficient evaluation of headlamp designs.
Friederike B.
Last position:
Independent Consultant and Trainer at Friederike Bohm Consulting
- Consulting on lean, logistics, AI applications and process optimization
- Customized concepts for digitalization, change & transformation
- Adaptive training and workshops for professionals and managers
Dean R.
Last position:
CEO / Chief Scientist at ENUM
- Blockchain platform technology
- Blockchain digital platform / Digital Economy.
Akshata N.
Last position:
Data Science Intern at Unified Mentor
- Improved predictive model accuracy by 18% using advanced feature engineering.
- Automated data pipelines via Python ETL, reducing manual work by 25%.
- Documented data flows to identify automation potential and support digitalization projects.
Divij W.
Last position:
Data Scientist at Daimler R&D, Daimler AG
- Mercedes Me is an app that connects your phone to several features in the car
- Implemented analytical KPIs for the Digital Drivers Log (Fahrtenbuch) feature
- Used PySpark on Databricks
Christoph D.
Last position:
Agentic RAG AI System at Financial Services Provider
- Developed an agentic RAG system to support the development organization.
- Technologies: Python, LangGraph, Qdrant, Claude Code, GitHub.
Augusto M.
Last position:
Managing Director/Co-Founder at Merx GmbH
- Responsible for data analytics and marketing/sales.
- This is a part-time job (1-2 days a week).
Discover over 15,000 top freelancers
Statistics of experts using Data Science
Aggregated from the professional profiles of matched freelancers.
Experience
16 years (Germany: 14 years)
Position duration
2.8 years (Germany: 2.2 years)
Positions per freelancer
8 (Germany: 9)
Top business areas
Business Intelligence, Information Technology, Product Development
Top industries
Automotive, Information Technology, Professional Services
Certification focus areas
Business Intelligence, Information Technology, Product Development
Bachelor's degree or higher
100% (Germany: 97%)
Master's degree or higher
88% (Germany: 80%)
Doctorate
13% (Germany: 22%)
Certifications per freelancer
2 (Germany: 3)
Most common languages
German, English, French
Speak two or more languages
100% (Germany: 97%)
Based on our profile pool as of 29 Oct 2026.
Daily rate distribution
The chart shows how the daily rates of experts in this technology in Stuttgart are distributed, based on recent contracts on our platform. Each bar covers a rate range — its height shows the share of experts charging within that range.
Average rates of experts in Stuttgart using Data Science
Rates are based on recent contracts and do not include FRATCH margin.
The average daily rate is the mean of all daily rates from recent contracts of comparable freelancers on our platform.
The median daily rate is the middle value of all daily rates — half of comparable freelancers charge less, half charge more. Unlike the average, it is barely affected by outliers.
Calculated based on our freelancers’ daily rates as of 29 Oct 2026. Actual rates may vary depending on seniority level, experience, skill specialization, project complexity, and engagement length.
Data Science experts industry focus
See which industries our matched freelancers work in most often — every figure is calculated live from the freelancers on FRATCH.
- Automotive (78%)
- Information Technology (67%)
- Professional Services (56%)
- Education (44%)
- Banking and Finance (44%)
- Transportation (44%)
- Manufacturing (44%)
- Healthcare (33%)
Please note that freelancers can work across multiple industries, so percentages overlap.
About the technology
What Data Science covers
Data Science combines statistics, programming, domain knowledge and machine learning to extract useful evidence from structured and unstructured data. Specialists explore data, define measurable questions and create models that support decisions, automate predictions or reveal patterns. The work spans the full path from raw data to a usable result.
Models and deliverables
Professionals turn business questions into tested analytical products. Typical deliverables include:
- Demand, churn and risk prediction models
- Recommendation and ranking systems
- Customer segmentation and anomaly detection
- Forecasting dashboards and decision tools
- Reproducible notebooks, APIs and model documentation
The right approach depends on data quality, decision speed, explainability and how the result will be used in production.
Ecosystem and tooling
Python is central to many Data Science projects, with pandas, NumPy, scikit-learn and notebooks used for analysis and modelling. Specialists may also work with PyTorch or TensorFlow for deep learning, SQL for data access, and Spark for distributed processing. Cloud services, Git, Docker, MLflow and orchestration tools support repeatable workflows and deployment.
When companies need specialists
Companies bring in freelance expertise when internal teams need focused analytical capacity or a project requires skills that are not available in-house. Common signals include:
- Important data is spread across disconnected systems
- Forecasts or manual decisions are no longer reliable
- A prototype must become a monitored service
- Models need validation, documentation or explainability
In Stuttgart, this work can support mobility, manufacturing, engineering, finance and life sciences. Remote collaboration is often practical when data access and stakeholder routines are clearly arranged.
Adjacent capabilities
Strong professionals connect modelling with the systems around it. They understand data pipelines, warehouse design, experiment tracking, software testing and deployment, not just algorithms. Depending on the assignment, useful adjacent skills include MLOps, business intelligence, natural language processing, computer vision, causal analysis and data governance.
A specialist should also translate findings for product, operations and leadership teams. Clear assumptions, limitations and recommendations matter as much as model performance.
What quality looks like
Quality starts with a precise problem definition and a representative data set. Experienced specialists establish a meaningful baseline, prevent leakage, choose metrics that reflect the business decision and test performance on unseen data. They examine bias, robustness, interpretability and the cost of false results.
Look for a professional who can explain trade-offs without hiding uncertainty, document the workflow and define how the model will be monitored after delivery. A strong result is reproducible, maintainable and useful to the people who rely on it.
Frequently asked questions
Key details about Data Science, drawn from the questions we get asked most.
Data Science is used to analyse data and support better decisions with evidence. Companies apply it to forecasting, fraud detection, recommendations, customer analysis, quality control, pricing and operational planning.
Data Science typically goes beyond reporting historical performance. It uses statistical analysis and machine learning to predict outcomes, discover hidden patterns and test possible actions, while business intelligence usually focuses on trusted metrics, dashboards and descriptive analysis.
A strong Data Science specialist combines statistics, Python, SQL, data preparation and model evaluation. Depending on the assignment, experience with cloud data platforms, MLOps, NLP, computer vision, experiment design or domain-specific analytics may also be important.
The required level depends on the risk, data condition and delivery stage. A focused analysis may need a specialist who can work independently with messy data, while a production model requires deeper experience with deployment, monitoring, security and communication across teams.
Data Science work is often suitable for remote collaboration when secure data access, documentation and regular stakeholder sessions are in place. On-site workshops in Stuttgart can help with discovery, domain context and adoption, especially in manufacturing or operational environments.
Data Science and traditional statistics are not competing choices in every project. Statistics is essential for inference, uncertainty and experimental design, while Data Science often adds software practices, large-scale data handling and predictive modelling; the best approach follows the decision to be made.
Ask a Data Science freelancer to explain the business question, baseline, data limitations and evaluation method behind a previous result. Good professionals discuss leakage, bias, uncertainty, reproducibility and monitoring instead of presenting model accuracy without context.
Before Data Science modelling begins, the team should define the decision, available data, target outcome and success criteria. Access rules, data ownership, labelling quality and a realistic plan for using the result in operations are equally important.
The average hourly rate of freelancers in Stuttgart, Germany who have used Data Science in their recent projects is 100 €, which corresponds to a daily rate of about 801 € based on an 8-hour working day.
Of the freelancers in Stuttgart, Germany who have used Data Science in their recent projects, 100% hold at least a Bachelor's degree, 88% hold at least a Master's degree, and 13% hold a doctorate.
On average, freelancers in Stuttgart, Germany who have used Data Science in their recent projects have 16 years of professional experience, with a single engagement typically lasting around 2.8 years.
The most common languages among freelancers in Stuttgart, Germany who have used Data Science in their recent projects are German (100%), English (100%), and French (22%).
The most common industries among freelancers in Stuttgart, Germany who have used Data Science in their recent projects are Automotive (78%), Information Technology (67%), and Professional Services (56%).
The most common business areas among freelancers in Stuttgart, Germany who have used Data Science in their recent projects are Business Intelligence (89%), Information Technology (78%), and Product Development (78%).
Main locations of FRATCH Experts, who have recently used Data Science
Our freelancers and interim experts are at home across the DACH region — available on-site in the major business hubs or fully remote. Choose a location to discover matched specialists, local market insights and up-to-date availability.
Berlin 
Hamburg 
Munich 
Cologne 
Frankfurt 
Dusseldorf 
Nuremberg Countries:
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